Artificial intelligence has developed rapidly in recent years, and the next development will be based on the automatic establishment of context. The current artificial intelligence is not mature enough, and the classification and pattern recognition it does not consider the context behind it.
According to the report, the first wave of artificial intelligence is still confined to the inference of some problems, there is no learning ability, and it can not deal with uncertainty; the second wave of artificial intelligence has more cognitive, learning and reasoning, and today's hot face Department identification is to use statistical learning for training. The third wave of artificial intelligence technology is based on contextual adaptation and can automatically establish contextualized models.
In a limited context, it is valuable to get information through the Internet of Things (IoT) Sensors to build the overall environment. Mass resources can also be used to detect errors, including Google Translate, as well as Facebook, Google, Yelp, and Amazon's suggestion system. This means that when users find that some of the results are unsatisfactory, they will be fed back to the labor. smart system.
Many warehouses and factories are currently creating environments where artificial intelligence and robots can operate. In the past few years, the second wave of artificial intelligence has enabled cars to have automatic driving capabilities, allowing machines to correctly identify images and sounds, and to allow computers to defeat top players in go tournaments. This is all due to the development of adaptive machine learning.
Train a large amount of data to find out the patterns of data and link these patterns. For example, in the medical field, experts pair genes with medical record data; in the manufacturing field, each product, machine, raw material, and process can be analyzed.
Modulating artificial intelligence and reusing these components for repeated training can accelerate the development of artificial intelligence. All walks of life are working hard to use artificial intelligence for more contexts and related developments will be faster and faster.
DeviceNet is a fieldbus standard used in automation technology, developed by Allen-Bradley company in 1994. DeviceNet uses controller Local Area network (CAN) as its underlying communication protocol, and its application layer has profiles defined for different devices. Major applications include information interchange, security equipment and large control systems.
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